3,573 research outputs found
Gossip Algorithms for Distributed Signal Processing
Gossip algorithms are attractive for in-network processing in sensor networks
because they do not require any specialized routing, there is no bottleneck or
single point of failure, and they are robust to unreliable wireless network
conditions. Recently, there has been a surge of activity in the computer
science, control, signal processing, and information theory communities,
developing faster and more robust gossip algorithms and deriving theoretical
performance guarantees. This article presents an overview of recent work in the
area. We describe convergence rate results, which are related to the number of
transmitted messages and thus the amount of energy consumed in the network for
gossiping. We discuss issues related to gossiping over wireless links,
including the effects of quantization and noise, and we illustrate the use of
gossip algorithms for canonical signal processing tasks including distributed
estimation, source localization, and compression.Comment: Submitted to Proceedings of the IEEE, 29 page
Nested Distributed Gradient Methods with Adaptive Quantized Communication
In this paper, we consider minimizing a sum of local convex objective
functions in a distributed setting, where communication can be costly. We
propose and analyze a class of nested distributed gradient methods with
adaptive quantized communication (NEAR-DGD+Q). We show the effect of performing
multiple quantized communication steps on the rate of convergence and on the
size of the neighborhood of convergence, and prove R-Linear convergence to the
exact solution with increasing number of consensus steps and adaptive
quantization. We test the performance of the method, as well as some practical
variants, on quadratic functions, and show the effects of multiple quantized
communication steps in terms of iterations/gradient evaluations, communication
and cost.Comment: 9 pages, 2 figures. arXiv admin note: text overlap with
arXiv:1709.0299
Quantized Consensus ADMM for Multi-Agent Distributed Optimization
Multi-agent distributed optimization over a network minimizes a global
objective formed by a sum of local convex functions using only local
computation and communication. We develop and analyze a quantized distributed
algorithm based on the alternating direction method of multipliers (ADMM) when
inter-agent communications are subject to finite capacity and other practical
constraints. While existing quantized ADMM approaches only work for quadratic
local objectives, the proposed algorithm can deal with more general objective
functions (possibly non-smooth) including the LASSO. Under certain convexity
assumptions, our algorithm converges to a consensus within
iterations, where depends on the local
objectives and the network topology, and is a polynomial determined by
the quantization resolution, the distance between initial and optimal variable
values, the local objective functions and the network topology. A tight upper
bound on the consensus error is also obtained which does not depend on the size
of the network.Comment: 30 pages, 4 figures; to be submitted to IEEE Trans. Signal
Processing. arXiv admin note: text overlap with arXiv:1307.5561 by other
author
A Gossip Algorithm based Clock Synchronization Scheme for Smart Grid Applications
The uprising interest in multi-agent based networked system, and the numerous
number of applications in the distributed control of the smart grid leads us to
address the problem of time synchronization in the smart grid. Utility
companies look for new packet based time synchronization solutions with Global
Positioning System (GPS) level accuracies beyond traditional packet methods
such as Network Time Proto- col (NTP). However GPS based solutions have poor
reception in indoor environments and dense urban canyons as well as GPS antenna
installation might be costly. Some smart grid nodes such as Phasor Measurement
Units (PMUs), fault detection, Wide Area Measurement Systems (WAMS) etc.,
requires synchronous accuracy as low as 1 ms. On the other hand, 1 sec accuracy
is acceptable in management information domain. Acknowledging this, in this
study, we introduce gossip algorithm based clock synchronization method among
network entities from the decision control and communication point of view. Our
method synchronizes clock within dense network with a bandwidth limited
environment. Our technique has been tested in different kinds of network
topologies- complete, star and random geometric network and demonstrated
satisfactory performance
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